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DATAR

12.11.2018 I DOMENICO TARABORRELLI (IEK-8)

Data science Aspects and Tools in Atmospheric Research

(2)

MOTIVATION

•Observational data sets are sparse either in time and space or in terms of chemical composition, e.g. airborne field campaigns.

(3)

MOTIVATION

•Observational data sets are sparse either in time and space or in terms of chemical composition, e.g. airborne field campaigns.

•Quantitative assessment of the interplay between atmospheric composition and weather/climate requires the use of multiple complementary datasets, e.g.

simulation output and trace gas retrievals.

(4)

MOTIVATION

•Observational data sets are sparse either in time and space or in terms of chemical composition, e.g. airborne field campaigns.

•Quantitative assessment of the interplay between atmospheric composition and weather/climate requires the use of multiple complementary datasets, e.g.

simulation output and trace gas retrievals.

•This requirement poses certain demands on the data science abilities of next- generation atmospheric scientists.

(5)

MOTIVATION

A dramatization

Yerkes-Dodson law

Automation

Information underload

↓

Erosion of talent Shallow thinking

Little automation Information overload

↓

Divided attention Shallow thinking

flow

(6)

CONCEPT

A short-course introducing to:

•the basics of data and their lifecycle

•common tools for the analysis of atmospheric data

•various large datasets in environmental sciences

•various applications in atmospheric sciences

•a glossary comprising many relevant definitions and concepts

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DATA BASICS AND LIFECYCLE

•Kinds of data (Schröder, IEK-8)

•Data standards (Schröder/Rosanka, IEK-8)

•Data lifecycle (PD Dr. Schultz)

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DATA PROCESSING AND ANALYSIS

•Data quality assurance and control (Dr. Rohs, IEK-8)

•Tools for data analysis (Schröder/Rosanka, IEK-8)

(9)

LARGE DATASETS AND DATA ANALYTICS

•Large datasets in atmospheric sciences (PD Dr. Schultz, JSC)

•Databases of atmospheric kinetic data (Dr. Vereecken, IEK-8)

•Large data infrastructures in environmental sciences (PD Dr. Petzold, IEK-8)

•Web services for data distribution (Dr. Stein, JSC)

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APPLICATIONS IN ATMOSPHERIC SCIENCE

•Field campaign planning (Dr. Grooß, IEK-7)

•Satellite retrievals 1 (Dr. Ungermann, IEK-7)

•Satellite retrievals 2(PD Dr. von Clarmann, KIT)

•Visualization of climate data with ParaView (Dr. Zilken, JSC)

(11)

STAY ON TOP!

flow

Referenzen

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